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R_references.txt
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+----------------------------------------------------+---------------------+-------------------------------------------------------+--------------------------------------------------------------+
| Text References |
+----------------------------------------------------+---------------------+-------------------------------------------------------+--------------------------------------------------------------+
| Title | Author | Reference | Description |
+----------------------------------------------------+---------------------+-------------------------------------------------------+--------------------------------------------------------------+
| Data Manipulation with R | Phil Spector | [Spe08] | A deeper review of many of the data manipulation topics |
| | | | covered in the previous section, and an introduction to |
| | | | several techniques not covered. |
+----------------------------------------------------+---------------------+-------------------------------------------------------+--------------------------------------------------------------+
| R in a Nutshell | Joseph Adler | [Adl10] | A detailed exploration of all of R’s base functions. |
| | | | This book takes the R manual and adds several practical |
| | | | examples. |
+----------------------------------------------------+---------------------+-------------------------------------------------------+--------------------------------------------------------------+
| Introduction to Scientific | Owen Jones, | [JMR09] | Unlike other introductory texts to R, this book |
| Programming and Simulation | Robert Maillardet | | focuses on the primacy of learning the language |
| Using R | and Andrew Robinson | | first, then creating simulations. |
+----------------------------------------------------+---------------------+-------------------------------------------------------+--------------------------------------------------------------+
| Data Analysis Using Regression and | Andrew Gelman and | [GH06] | This text is heavily focused on doing statistical |
| Multilevel/Hierarchical Models | Jennifer Hill | | analyses, but all of the examples are in R, and it |
| | | | is an excellent resource for learning both the |
| | | | language and methods. |
+----------------------------------------------------+---------------------+-------------------------------------------------------+--------------------------------------------------------------+
| ggplot2: Elegant Graphics for | Hadley Wickham | [Wic09] | The definitive guide to creating |
| Data Analysis | | | data visualizations with ggplot2 . |
| | | | |
| | | | |
| | | | |
| | | | |
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+----------------------------------------------------+---------------------+-------------------------------------------------------+--------------------------------------------------------------+
| Online references |
+-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
| Title | Author | Reference | Description |
+----------------------------------------------------+---------------------+-------------------------------------------------------+--------------------------------------------------------------+
| An Introduction to R | Bill Venables and | http://cran.r-project.org/doc/manuals/R-intro.html | An extensive and ever-changing introduction |
| | David Smith | | to the language from the R Core Team. |
+----------------------------------------------------+---------------------+-------------------------------------------------------+--------------------------------------------------------------+
| The R Inferno | Patrick Burns | http://lib.stat.cmu.edu/S/Spoetry/Tutor/R_inferno.pdf | An excellent introduction to R for the |
| | | | experienced programmer.The abstract says |
| | | | it best: “If you are using R and you think |
| | | | you’re in hell, this is a map for you.” |
+----------------------------------------------------+---------------------+-------------------------------------------------------+--------------------------------------------------------------+
| R for Programmers | Norman Matloff | http://heather.cs.ucdavis.edu/~matloff/R/RProg.pdf | Similar to The R Inferno, this introduction is geared toward |
| | | | programmers with experience in other languages. |
+----------------------------------------------------+---------------------+-------------------------------------------------------+--------------------------------------------------------------+
| The Split-Apply-Combine Strategy for Data Analysis | Hadley Wickham | http://www.jstatsoft.org/v40/i01/paper | The author of plyr provides an excellent introduction to |
| | | | the map-reduce paradigm in the context of his tools, with |
| | | | many examples. |
+----------------------------------------------------+---------------------+-------------------------------------------------------+--------------------------------------------------------------+
| R Data Analysis Examples | UCLA Academic | http://www.ats.ucla.edu/stat/r/dae/default.htm | A great “Rosetta Stone”-style introduction for those |
| | Technology Services | | with experience in other statistical programming platforms, |
| | | | such as SAS, SPSS,and Stata. |
+----------------------------------------------------+---------------------+-------------------------------------------------------+--------------------------------------------------------------+
| | | | |
+----------------------------------------------------+---------------------+-------------------------------------------------------+--------------------------------------------------------------+